Does it support advanced plots like UMAP or Heatmaps?

Yes, the skill includes specific implementation patterns for complex visualizations like UMAP projections, genomic heatmaps, and volcano plots.

Can I export plots for academic journals?

Yes, the skill includes configurations for high-resolution output (300 DPI) and vector-friendly formatting suitable for publication.

Does this skill require a specific cloud environment?

No, this skill is designed to run locally in your own Python environment, making it compatible with any local dataset and ensuring data privacy.

Which Python libraries are required?

You will need matplotlib, seaborn, pandas, and numpy installed in your environment to use these visualization patterns.

Data Visualization Plots

Name: Data Visualization Plots
Author: Microck

byMicrock

•

Data Science & ML

Generates publication-quality scientific visualizations and data plots locally using Python's Matplotlib and Seaborn libraries.

This skill empowers Claude to create professional-grade figures, ranging from basic scatter and line plots to complex multi-panel heatmaps and volcano plots. By executing Python code locally within the user's environment, it bypasses the limitations of cloud-hosted sandboxes, allowing for high-resolution exports and detailed customization of aesthetics, fonts, and styles. It is particularly valuable for researchers and data scientists performing Exploratory Data Analysis (EDA) or preparing figures for academic publication and technical presentations.

Key Features

01Comprehensive plot library: Scatter, line, bar, box, violin, and heatmaps.

02Publication-ready quality: High-DPI (300+) export settings and professional styling templates.

03Scientific domain support: Specific templates for UMAP/tSNE, QC metrics, and Volcano plots.

04Local environment execution: Full control over data privacy and integration with local CSV/Parquet files.

05Advanced layouts: Support for multi-panel figures using Matplotlib GridSpec.

0681 GitHub stars

Use Cases

01Automating Exploratory Data Analysis (EDA) to visualize gene expression or QC metrics.

02Creating high-resolution figures for research papers and academic presentations.

03Generating multi-panel dashboards to visualize clustering results and differential expression.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add microck/ordinary-claude-skills data-viz-plots

For use in Claude.ai and ChatGPT

Download Skill